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Development of Autonomous Mobile Robot Based on Accurate Map in the Tsukuba Challenge 2014

机译:2014年筑波挑战赛中基于精确地图的自主移动机器人的开发

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We describe a navigation method for autonomous mobile robots and detail knowledge obtained through Tsukuba Challenge 2014 trial runs. The challenge requires robots to navigate autonomously 1.4 km in an urban area and to search for five persons in three areas. Accurate maps are important tools in localization on complex courses in autonomous outdoor navigation. We constructed an occupancy grid map using laser scanners, gyro-assisted odometry and a differential global positioning system (DGPS). In this study, we use maps as a graphical interface. Namely, by using maps, we give environmental information, untravelable low objects such as curb stones, and areas in nonsearches for "target" persons. For the purpose of increasing the map reusability, we developed a way-point editor, which can modify waypoints on maps to fit a course to a situation. We also developed a velocity control method that the robot uses to follow pedestrians and other robot by keeping safety distance on the course. As a result, our robot took part five of seven official trial runs to get to the goal. This indicates that the autonomous navigation method was stable in the Tsukuba Challenge 2014 urban environment.
机译:我们将介绍自主移动机器人的导航方法,以及通过Tsukuba Challenge 2014试运行获得的详细知识。这一挑战要求机器人在市区内自主导航1.4公里,并在三个地区寻找5个人。准确的地图是自动户外导航中复杂课程本地化的重要工具。我们使用激光扫描仪,陀螺仪辅助测距法和差分全球定位系统(DGPS)构造了占用栅格图。在这项研究中,我们使用地图作为图形界面。即,通过使用地图,我们可以提供环境信息,不可移动的低矮物体(例如路缘石)以及无法搜索“目标”人员的区域。为了提高地图的可重用性,我们开发了一个航点编辑器,该编辑器可以修改地图上的航点以适应特定情况。我们还开发了一种速度控制方法,该机器人可通过在路线上保持安全距离来跟随行人和其他机器人。结果,我们的机器人参加了七次正式试运行中的第五次以达到目标。这表明在2014年筑波挑战赛的城市环境中,自主导航方法是稳定的。

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